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Sameer Antani, PhD

About

Research Interests

Dr. Sameer Antani is a Principal Investigator (Tenure-Track) in the Division of Intramural Research of the National Library of Medicine (NLM) at the National Institutes of Health (NIH). He earned his Ph.D. and M.Eng. in Computer Science and Engineering from the Pennsylvania State University and his B.E. (First Class with Distinction) in Computer Engineering from the Savitribai Phule Pune University (formerly University of Pune), India. Dr. Antani is a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), Fellow of Institute of Electrical and Electronics Engineers (IEEE), and Senior Member of the SPIE. His research focuses on novel algorithms in medical imaging and multimodal machine learning (ML) and artificial intelligence (AI), ML/AI for resource-limited and global health settings, and characterizing data and innovations in ML/AI algorithm design for reliable AI predictions with applications in disease screening, diagnostics, risk prediction, and treatment. His scientific contributions and research leadership have been recognized through several awards including NLM Board of Regents Awards and NIH Director's Awards.

Publications

Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani S. Semantically redundant training data removal and deep model classification performance: A study with chest X-rays. Comput Med Imaging Graph. 2024 Jul;115:102379. doi: 10.1016/j.compmedimag.2024.102379. Epub 2024 Apr 9. PubMed PMID: 38608333; PubMed Central PMCID: PMC11144082.

Spirnak JR, Antani S. The Need for Artificial Intelligence Curriculum in Military Medical Education. Mil Med. 2024 May 18;189(5-6):954-958. doi: 10.1093/milmed/usad412. PubMed PMID: 37864817; PubMed Central PMCID: PMC11439989.

Xue Z, Oguguo T, Yu KJ, Chen TC, Hua CH, Kang CJ, Chien CY, Tsai MH, Wang CP, Chaturvedi AK, Antani S. Cleaning and Harmonizing Medical Image Data for Reliable AI: Lessons Learned from Longitudinal Oral Cancer Natural History Study Data. Proc SPIE Int Soc Opt Eng. 2024 Feb;12931. doi: 10.1117/12.3005875. Epub 2024 Apr 2. PubMed PMID: 38774479; PubMed Central PMCID: PMC11107840.

Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani S. Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric chest X-ray images. PLOS Digit Health. 2024 Jan;3(1):e0000286. doi: 10.1371/journal.pdig.0000286. eCollection 2024 Jan. PubMed PMID: 38232121; PubMed Central PMCID: PMC10793885.

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